METHODS: DNA samples from 92 patients and 156 healthy controls collected from two medical centers in Riyadh, Saudi Arabia were analyzed for four regions located at X-chromosome using the Investigator® Argus X-12 QS Kit.
RESULTS: The results demonstrated that microvariant alleles of (DXS7132, DXS10146, HPRTB, DXS10134, and DXS10135) are overrepresented in the BPH group (p < 0.00001). Allele 28 of DXS10135 and allele 15 of DXS7423 could have a protective effect, OR 0.229 (95%CI, 0.066-0.79); and OR 0.439 (95%CI, 0.208-0.925). On the other hand, patients carrying allele 23 of DXS10079 and allele 26 of DXS10148 presented an increased risk to PrCa OR 4.714 (95%CI, 3.604-6.166).
CONCLUSION: The results are in concordance with the involvement of the X chromosome in PrCa and BPH development. STR allele studies may add further information from the definition of a genetic profile of PrCa resistance or susceptibility. As TBL1, AR, LDOC1, and RPL10 genes are located at regions Xp22.31, Xq11.2-12, Xq26.2, and Xq28, respectively, these genes could play an essential role in PrCa or BPH.
OBJECTIVE: To report the first year's screening results for all men at enrollment in the study.
DESIGN, SETTING AND PARTICIPANTS: We recruited men aged 40-69 yr with germline BRCA1/2 mutations and a control group of men who have tested negative for a pathogenic BRCA1 or BRCA2 mutation known to be present in their families. All men underwent prostate-specific antigen (PSA) testing at enrollment, and those men with PSA >3 ng/ml were offered prostate biopsy.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: PSA levels, PCa incidence, and tumour characteristics were evaluated. The Fisher exact test was used to compare the number of PCa cases among groups and the differences among disease types.
RESULTS AND LIMITATIONS: We recruited 2481 men (791 BRCA1 carriers, 531 BRCA1 controls; 731 BRCA2 carriers, 428 BRCA2 controls). A total of 199 men (8%) presented with PSA >3.0 ng/ml, 162 biopsies were performed, and 59 PCas were diagnosed (18 BRCA1 carriers, 10 BRCA1 controls; 24 BRCA2 carriers, 7 BRCA2 controls); 66% of the tumours were classified as intermediate- or high-risk disease. The positive predictive value (PPV) for biopsy using a PSA threshold of 3.0 ng/ml in BRCA2 mutation carriers was 48%-double the PPV reported in population screening studies. A significant difference in detecting intermediate- or high-risk disease was observed in BRCA2 carriers. Ninety-five percent of the men were white, thus the results cannot be generalised to all ethnic groups.
CONCLUSIONS: The IMPACT screening network will be useful for targeted PCa screening studies in men with germline genetic risk variants as they are discovered. These preliminary results support the use of targeted PSA screening based on BRCA genotype and show that this screening yields a high proportion of aggressive disease.
PATIENT SUMMARY: In this report, we demonstrate that germline genetic markers can be used to identify men at higher risk of prostate cancer. Targeting screening at these men resulted in the identification of tumours that were more likely to require treatment.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
METHODS: Immunoblotting, immunofluorescence, quantitative real-time PCR and flow cytometry assays investigated the expression of E-cadherin and CXCR3 isoforms. Intrasplenic inoculation of human prostate cancer (PCa) cells with spontaneous metastasis to the liver analyzed E-cadherin and CXCR3-B expression during cancer progression in vivo.
RESULTS: We found reciprocal regulation of E-cadherin and CXCR3 isoforms. E-cadherin surface expression promoted CXCR3-B presentation on the cell membrane, and to a lesser extent increased its mRNA and total protein levels. In turn, forced expression of CXCR3-A reduced E-cadherin expression level, whereas CXCR3-B increased E-cadherin in PCa. Meanwhile, a positive correlation of E-cadherin and CXCR3-B expression was found both in experimental PCa liver micro-metastases and patients' tissue.
CONCLUSIONS: CXCR3-B and E-cadherin positively correlated in vitro and in vivo in PCa cells and liver metastases, whereas CXCR3-A negatively regulated E-cadherin expression. These results suggest that CXCR3 isoforms may play important roles in cancer progression and dissemination via diametrically regulating tumor's phenotype.
METHODS: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).
RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.
CONCLUSIONS: ABO blood type was not associated with risk of aggressive prostate cancer.
METHODS: PSAV was calculated using logistic regression to determine if PSA or PSAV predicted the result of prostate biopsy (PB) in men with elevated PSA values. Cox regression was used to determine whether PSA or PSAV predicted PSA elevation in men with low PSAs. Interaction terms were included in the models to determine whether BRCA status influenced the predictiveness of PSA or PSAV.
RESULTS: 1634 participants had ⩾3 PSA readings of whom 174 underwent PB and 45 PrCas diagnosed. In men with PSA >3.0 ng ml-l, PSAV was not significantly associated with presence of cancer or high-grade disease. PSAV did not add to PSA for predicting time to an elevated PSA. When comparing BRCA1/2 carriers to non-carriers, we found a significant interaction between BRCA status and last PSA before biopsy (P=0.031) and BRCA2 status and PSAV (P=0.024). However, PSAV was not predictive of biopsy outcome in BRCA2 carriers.
CONCLUSIONS: PSA is more strongly predictive of PrCa in BRCA carriers than non-carriers. We did not find evidence that PSAV aids decision-making for BRCA carriers over absolute PSA value alone.
MATERIALS AND METHODS: MicroRNA software predicted that miR21 targets VCL while miR29a targets CX3CL1. Twenty benign prostatic hyperplasia (BPH) and 16 high grade CaP formalinfixed paraffin embedded (FFPE) specimens were analysed. From the bone scan results, high grade CaP samples were further classified into CaP with no BM and CaP with BM. Transient transfection with respective microRNA inhibitors was done in both RWPE1 (normal) and PC3 cell lines. QPCR was performed in all FFPE samples and transfected cell lines to measure VCL and CX3CL1 levels.
RESULTS: QPCR confirmed that VCL messenger RNA (mRNA) was significantly down regulated while CX3CL1 was upregulated in all FFPE specimens. Transient transfection with microRNA inhibitors in PC3 cells followed by qPCR of the targeted genes showed that VCL mRNA was significantly up regulated while CX3CL1 mRNA was significantly downregulated compared to the RWPE1 case.
CONCLUSIONS: The downregulation of VCL in FFPE specimens is most likely regulated by miR21 based on the in vitro evidence but the exact mechanism of how miR21 can regulate VCL is unclear. Upregulated in CaP, CX3CL1 was found not regulated by miR29a. More microRNA screening is required to understand the regulation of this chemokine in CaP with bone metastasis. Understanding miRNAmRNA interactions may provide additional knowledge for individualized study of cancers.